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检索条件"主题词=Change detection algorithms"

共 1584 条记录，以下是211-220 订阅

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Monitoring for Power-Line change and Outage detection in Smart Grid via the Alternating Direction Method of Multipliers

Monitoring for Power-Line Change and Outage Detection in Sma...

引用

International Conference on Advanced Information Networking and Applications Workshops (AINAW)

作者： Liang Zhao Wen-Zhan Song Lang Tong Yuan Wu Department of Computer Science Georgia State University Atlanta GA USA School of Electrical and Computer Engineering Cornell University Ithaca NY USA College of Information Engineering Zhejiang University of Technology Hangzhou China

A novel distributed line outage detection algorithm was developed in this paper through convex relaxation and alternating direction method of multipliers (ADMM) method for smart grid system. The devised approach allows identification of multiple line outages using limited number of PMU measurements. The diagnosis procedure is performed close to the place where PMU measurements are collected and only partial variable estimates are exchanged among the neighbours of processors. It is shown that the proposed method outperforms the existing methods, which are either suffering from computational complexity or security and privacy issues. Numerical tests demonstrated the merits of the proposed schemes in co-ordinately figuring out multiple line outages in the system.

关键词： Smart grids Vectors Phasor measurement units Educational institutions Covariance matrices change detection algorithms

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change detection using neural network in Toshka area

Change detection using neural network in Toshka area

引用

National Conference on Radio Science (NSRC)

作者： M. A. Fkirin S. M. Badwai Sayed A. Mohamed Department of Industrial Electronic Engineer and Control Faculty of Electronic Engineering Menoufia University Cairo Egypt National Authority슠for슠Remote Sensing and Space Sciences Cairo Egypt

The aim of this work is to investigate the applicability of using the neural network techniques in change detection of remotely sensed data. In addition, the tuning parameters of the network, such as encoding the output classes, adding the momentum term, and learning rate, are investigated in order to achieve best network performance. Neural network-based change detection system in this study is implemented using back propagation-training algorithm. This trained network is designed to be able to detect efficiently any variation between two images and provide adequate information about the type of changes. In an effort to meet these requirements, neural network scheme with improvement factor, leaning rate and momentum term is proposed to monitor environmental changes in Toshka area, Egypt. Two sets of satellite images with different dates are used, the first set contains of two sample satellite images, the second set of images acquired on 1984, 2000 and *** the output of the proposed model with the mostly used change detection techniques; ratio and classification, results show a great potential as the proposed scheme was able to identify not only the changed and non-changed area but also it was capable to identify the nature of these changes.

关键词： Neural networks change detection algorithms Satellite broadcasting Data engineering Artificial neural networks Neurons Remote sensing Monitoring Military satellites Algorithm design and analysis

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An automated change detection system

An automated change detection system

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： D. Sloggett C. Gurney W. Newton R. Gooding I. Dowman Earth Observation Sciences Limited Farnham Surrey UK Department of Photogrammetry and Surveying University College London London UK

The aim of the research described is to prototype algorithms which would form a suitable basis for an operational, automated map update system. Using forestry in the U.K as an example, algorithms were developed based on edge matching and object analysis which could be applied with or without a ground map and with various levels of user intervention. These were tested using Thematic Mapper data and digitised ground cover maps on the Elchies Forest near Elgin, Scotland. Where possible, results were augmented using evidential reasoning to reduce false alarms based on specific knowledge of forestry practice. Results indicate that even with the minimum of user intervention major areas of change can be detected. Increasing user intervention can reduce processing complexity and time, but is less suitable for an automated system. The paper presents the overall framework in which the techniques might be exploited.< >

关键词： change detection algorithms Forestry Prototypes Algorithm design and analysis Testing

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Application of Euclidean norm in multi-temporal remote sensing image change detection

Application of Euclidean norm in multi-temporal remote sensi...

引用

Congress on Image and Signal Processing, CISP

作者： Wei He Sichuan College of Architectural Technology Deyang China

This paper explores a methodology for computing the amount of changes that have occurred within an area by using remotely sensed technologies and Euclidean norm. The discussion concentrates on the formulation of a standard procedure that, using the Euclidean norm, can define the likelihood of changes detected from remotely sensed data. Furthermore, an example of how Euclidean norm can be employed in change detection and the selection of change threshold is presented. The example, which is carried out on a multitemporal remote-sensing data set, also confirms the effectiveness of the proposed system. And it indicates that the neighborhood has quite influence on the change detection of pixels information and can be regarded as an important factor to be introduced into quantitative model.

关键词： Pixel Entropy Remote sensing Euclidean distance Accuracy change detection algorithms Image color analysis

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A unified approach to scene change detection in uncompressed and compressed video

A unified approach to scene change detection in uncompressed...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： W.A.C. Fernando C.N. Canagarajah D.R. Bull Image Communications Group Centre for Communications Research University of Bristol Bristol UK

There is an urgent need to extract key information automatically from video for the purposes of indexing, fast retrieval and scene analysis. To support this vision, reliable scene change detection algorithms must be developed. This paper describes a novel unified algorithm for scene change detection in uncompressed and MPEG-2 compressed video sequences using statistical features of images. Results on video of various content types are reported and validated with the proposed scheme in uncompressed and MPEG-2 compressed video. Furthermore, results show that the accuracy of the detected transitions is above 95% and 90% for uncompressed and MPEG-2 compressed video respectively.

关键词： Layout Video compression Transform coding Image coding Data mining Indexing Information retrieval Image analysis detection algorithms change detection algorithms

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change detection in a 3-d World

Change Detection in a 3-d World

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Thomas Pollard Joseph L. Mundy Brown University Providence RI USA

This paper examines the problem of detecting changes in a 3-d scene from a sequence of images, taken by cameras with arbitrary but known pose. No prior knowledge of the state of normal appearance and geometry of object surfaces is assumed, and abnormal changes can occur in any image of the sequence. To the authors' knowledge, this paper is the first to address the change detection problem in such a general framework. Existing change detection algorithms that exploit multiple image viewpoints typically can detect only motion changes or assume a planar world geometry which cannot cope effectively with appearance changes due to occlusion and un-modeled 3-d scene geometry (ego-motion parallax). The approach presented here can manage the complications of unknown and sometimes changing world surfaces by maintaining a 3-d voxel-based model, where probability distributions for surface occupancy and image appearance are stored in each voxel. The probability distributions at each voxel are continuously updated as new images are received. The key question of convergence of this joint estimation problem is answered by a formal proof based on realistic assumptions about the nature of real world scenes. A series of experiments are presented that evaluate change detection accuracy under laboratory-controlled conditions as well as aerial reconnaissance scenarios.-

关键词： Layout Cameras Motion detection change detection algorithms detection algorithms Information geometry Probability distribution Image resolution Lighting Object detection

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A Study for Hyperspectral Anomaly change detection on “Viareggio 2013 Trial” Dataset

A Study for Hyperspectral Anomaly Change Detection on “Viar...

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International Workshop on the Analysis of Multi-temporal Remote Sensing Images (MultiTemp)

作者： Chen Wu Yukun Lin Bo Du Liangpei Zhang State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China Institute of Remote Sensing and Digital Earth University of Chinese Academy of Sciences Beijing China School of Computer Science Wuhan University Wuhan China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan P.R. China

Hyperspectral anomaly change detection aims at finding rare and anomalous changes in multi-temporal hyperspectral images. There are existing many works about anomaly change detection algorithms, whereas they are all proposed and evaluated on their own datasets. With the publication of “Viareggio 2013 Trial”, it is necessary to compare the state-of-the-art methods on this dataset with fully ground-truth references. In this paper, we compare 8 anomaly change detection methods on the two multi-temporal pairs of “Viareggio 2013 Trial”. The experimental results indicate that slow feature analysis with LCRA obtains the best performance.

关键词： Hyperspectral imaging Detectors change detection algorithms detection algorithms Feature extraction

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Fast-PCANet For Scene change detection

Fast-PCANet For Scene Change Detection

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IEEE International Conference of Intelligent Robotic and Control Engineering (IRCE)

作者： Siqi Shi Pengcheng Xia Nanting Li Youwei Yin School of Automation and Information Engineering Xi'an University of Technology Xi’an China Chongqing Fudi Lithium Battery Co. Ltd Chongqing China

ISBN: (数字)9798350352399

ISBN: (纸本)9798350352405

An efficient scene change detection algorithm based on Fast-PCANet is proposed. Given infrared and visible differential images, image blocks with candidate changed points can be distinguishes roughly from the unchanged pixel points by the calculated pixel classification threshold. As for Fast-PCANet which preserves detailed information and improves detection efficiency, feature maps of two principal component analysis convolutional layers are merged and concatenated to one dimensional feature vector, then a linear support vector machine is used to predict those changed pixels. The morphological closed operation and median filter are used to further correct false positives. For training Fast-PCANet, the proportion of negative samples is increased by sampling pseudo-changed points with a second-order arithmetic sequence, which can achieve the balance of between positive and negative samples. Experimental results shows the proposed algorithm effectively eliminates missed and false detection and and improves detection performance.

关键词： Training Support vector machines change detection algorithms Merging Feature extraction Vectors detection algorithms Robots Principal component analysis Arithmetic

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Spatio-Temporal change detection with Granger Causality Based Cluster Sequence Mining

Spatio-Temporal Change Detection with Granger Causality Base...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Nat Pavasant Masayuki Numao Ken-ichi Fukui Osaka University Japan The Institute of Scientific and Industrial Research Osaka University Japan

ISBN: (数字)9781728184708

ISBN: (纸本)9781728184715

We proposed a method to extract causal relations of clusters from multi-dimensional event sequence data, along with another method to detect the changes of the extracted relations over time. The proposed Granger Cluster Sequence Mining (GCSM) algorithm identifies the pairs of spatial data clusters that have causality over time with each other. It extends the Cluster Sequence Mining algorithm, which utilized a statistical inference technique to identify occurrence relation, with a causality based on Granger causality. We also proposed a statistical model to infer the changes over time of each extracted causal relation. With experiments using synthetic data and semi-real data, we confirmed that the algorithm works correctly, and able to extract the embedded causal relations with high F-score and high accuracy of change points.

关键词： Machine learning algorithms change detection algorithms Clustering algorithms Prediction algorithms Inference algorithms Spatial databases Data mining

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Geo-Spatial Object Data Analytics Based change detection in Aerial Imagery

Geo-Spatial Object Data Analytics Based Change Detection in ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Bishwajit Sharma Anima Mishra Sharma Arshad Jamal Centre for AI and Robotics (CAIR) C.V. Raman Nagar Bangalore India

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

change detection in remote sensing is indispensable for monitoring areas of interest. While radiometric changes depict seasonal and man-made changes appearing in each pixel, the comprehension of such changes are subjective and often limited to climate, geological or ecological studies. In a first, this work utilizes an object detection algorithm to create an object data layer per image, and compares this geospatial object data layer from imagery of two different times using data analytics. This results in a focused approach, where the seasonal variations, vegetation etc., do not distract the change detection process. The object classes, such as buildings, vehicle lots, etc, also provide a semantic understanding of the changes. The algorithm is tested on available aerial imagery datasets from two different dates, having different resolutions. A popular detection algorithm trained on the xView 60 class dataset is employed in this study.

关键词： Data analysis change detection algorithms Semantics Vegetation mapping Object detection Radiometry Spatial databases

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